Search results for: decomposition method

Authors: Ravneil Nand

Abstract:

Cooperative coevolution uses problem decomposition methods to solve a larger problem. The problem decomposition deals with breaking down the larger problem into a number of smaller sub-problems depending on their method. Different problem decomposition methods have their own strengths and limitations depending on the neural network used and application problem. In this paper we are introducing a new problem decomposition method known as Hidden-Neuron Level Decomposition (HNL). The HNL method is competing with established problem decomposition method in time series prediction. The results show that the proposed approach has improved the results in some benchmark data sets when compared to the standalone method and has competitive results when compared to methods from literature.

Keywords: cooperative coevaluation, feed forward network, problem decomposition, neuron, synapse

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Authors: M. S. H. Chowdhury, Ishak Hashim

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In this paper, linear and non-linear stiff systems of ordinary differential equations are solved by the classical Adomian decomposition method (ADM) and the multi-stage Adomian decomposition method (MADM). The MADM is a technique adapted from the standard Adomian decomposition method (ADM) where standard ADM is converted into a hybrid numeric-analytic method called the multistage ADM (MADM). The MADM is tested for several examples. Comparisons with an explicit Runge-Kutta-type method (RK) and the classical ADM demonstrate the limitations of ADM and promising capability of the MADM for solving stiff initial value problems (IVPs).

Keywords: stiff system of ODEs, Runge-Kutta Type Method, Adomian decomposition method, Multistage ADM

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Authors: Hamdy M. Youssef, Eman A. Al-Lehaibi

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This paper presents an iteration method for the numerical solutions of a one-dimensional problem of generalized thermoelasticity with one relaxation time under given initial and boundary conditions. The thermoelastic material with variable properties as a power functional graded has been considered. Adomian’s decomposition techniques have been applied to the governing equations. The numerical results have been calculated by using the iterations method with a certain algorithm. The numerical results have been represented in figures, and the figures affirm that Adomian’s decomposition method is a successful method for modeling thermoelastic problems. Moreover, the empirical parameter of the functional graded, and the lattice design parameter have significant effects on the temperature increment, the strain, the stress, the displacement.

Keywords: Adomian, decomposition method, generalized thermoelasticity, algorithm

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Authors: Ruomeng Xiao, Zhulin Zong, Longfa Yang

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Aiming at the problem that the target signal is difficult to detect under the strong ground clutter environment, this paper proposes a clutter suppression algorithm based on the combination of singular value decomposition and the Mallat fast wavelet algorithm. The method first carries out singular value decomposition on the radar echo data matrix, realizes the initial separation of target and clutter through the threshold processing of singular value, and then carries out wavelet decomposition on the echo data to find out the target location, and adopts the discard method to select the appropriate decomposition layer to reconstruct the target signal, which ensures the minimum loss of target information while suppressing the clutter. After the verification of the measured data, the method has a significant effect on the target extraction under low SCR, and the target reconstruction can be realized without the prior position information of the target and the method also has a certain enhancement on the output SCR compared with the traditional single wavelet processing method.

Keywords: clutter suppression, singular value decomposition, wavelet transform, Mallat algorithm, low SCR

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Authors: F. J. Adeyeye, D. Eni, K. M. Okedoye

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In this paper we present a Hybrid of Adomian decomposition method (ADM). This is the substitution of a One-step method of Taylor’s series approximation of orders I and II, into the nonlinear part of Adomian decomposition method resulting in a convergent series scheme. This scheme is applied to solve some Logistic problems represented as Abelian differential equation and the results are compared with the actual solution and Runge-kutta of order IV in order to ascertain the accuracy and efficiency of the scheme. The findings shows that the scheme is efficient enough to solve logistic problems considered in this paper.

Keywords: Adomian decomposition method, nonlinear part, one-step method, Taylor series approximation, hybrid of Adomian polynomial, logistic problem, Malthusian parameter, Verhulst Model

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Authors: Kuo-Teng Tsai, You-Min Huang

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In this study, the problem of a spiral fin with a period base temperature is analyzed by using the Adomian decomposition method. The Adomian decomposition method is a useful and practice method to solve the nonlinear energy equation which are associated with the heat radiation. The period base temperature is around a mean value. The results including the temperature distribution and the heat flux from the spiral fin base can be calculated directly. The results also discussed the effects of the dimensionless variables for the temperature variations and the total energy transferred from the spiral fin base.

Keywords: spiral fin, period, adomian decomposition method, nonlinear

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Authors: Samah Benmerbi, Kamal Amroun, Abdelkamel Tari

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The increasing number of Web service (WS)providers throughout the globe, have produced numerous Web services providing the same or similar functionality. Therefore, there is a need of tools developing the best answer of queries by selecting and composing services with total transparency. This paper reviews various QoS based Web service selection mechanisms and architectures which facilitate qualitatively optimal selection, in other fact Web service composition is required when a request cannot be fulfilled by a single web service. In such cases, it is preferable to integrate existing web services to satisfy user’s request. We introduce an automatic Web service composition method based on hypergraph decomposition using hypertree decomposition method. The problem of selection and the composition of the web services is transformed into a resolution in a hypertree by exploring the relations of dependency between web services to get composite web service via employing an execution order of WS satisfying global request.

Keywords: web service, web service selection, web service composition, QoS, hypergraph decomposition, BE hypergraph decomposition, hypertree resolution

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Authors: R. B. Ogunrinde, C. C. Jibunoh

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In this paper, a spectral decomposition method is developed for the direct integration of stiff and nonstiff homogeneous linear (ODE) systems with linear, constant, or zero right hand sides (RHSs). The method does not require iteration but obtains solutions at any random points of t, by direct evaluation, in the interval of integration. All the numerical solutions obtained for the class of systems coincide with the exact theoretical solutions. In particular, solutions of homogeneous linear systems, i.e. with zero RHS, conform to the exact analytical solutions of the systems in terms of t.

Keywords: spectral decomposition, linear RHS, homogeneous linear systems, eigenvalues of the Jacobian

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Authors: Hamdy M. Youssef, Eman A. Al-Lehaibi

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Due to many applications and problems in the fields of plasma physics, geophysics, and other many topics, the interaction between the strain field and the magnetic field has to be considered. Adomian introduced the decomposition method for solving linear and nonlinear functional equations. This method leads to accurate, computable, approximately convergent solutions of linear and nonlinear partial and ordinary differential equations even the equations with variable coefficients. This paper is dealing with a mathematical model of generalized thermoelasticity of a half-space conducting medium. A magnetic field with constant intensity acts normal to the bounding plane has been assumed. Adomian’s decomposition method has been used to solve the model when the bounding plane is taken to be traction free and thermally loaded by harmonic heating. The numerical results for the temperature increment, the stress, the strain, the displacement, the induced magnetic, and the electric fields have been represented in figures. The magnetic field, the relaxation time, and the angular thermal load have significant effects on all the studied fields.

Keywords: Adomian’s decomposition method, magneto-thermoelasticity, finite conductivity, iteration method, thermal load

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Authors: Y. J. Song, Q. S. Xu, X. C. Wang, H. Wang, C. Q. Li

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The catalyst of copper oxide loaded on HZSM-5 was developed for nitrous oxide (N₂O) direct decomposition. The kinetic of nitrous oxide decomposition was studied for CuO/HZSM-5 catalyst prepared by incipient wetness impregnation method. The external and internal diffusion of catalytic reaction were considered in the investigation. Experiment results indicated that the external diffusion was basically eliminated when the reaction gas mixture gas hourly space velocity (GHSV) was higher than 9000h⁻¹ and the influence of the internal diffusion was negligible when the particle size of the catalyst CuO/HZSM-5 was small than 40-60 mesh. The experiment results showed that the kinetic of catalytic decomposition of N₂O was a first-order reaction and the activation energy and the pre-factor of the kinetic equation were 115.15kJ/mol and of 1.6×109, respectively.

Keywords: catalytic decomposition, CuO/HZSM-5, kinetic, nitrous oxide

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Authors: M. M. Qasaymeh, M. A. Khodeir

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Subspace channel estimation methods have been studied widely. It depends on subspace decomposition of the covariance matrix to separate signal subspace from noise subspace. The decomposition normally is done by either Eigenvalue Decomposition (EVD) or Singular Value Decomposition (SVD) of the Auto-Correlation matrix (ACM). However, the subspace decomposition process is computationally expensive. In this paper, the multipath channel estimation problem for a Slow Frequency Hopping (SFH) system using noise space based method is considered. An efficient method to estimate multipath the time delays basically is proposed, by applying MUltiple Signal Classification (MUSIC) algorithm which used the null space extracted by the Rank Revealing LU factorization (RRLU). The RRLU provides accurate information about the rank and the numerical null space which make it a valuable tool in numerical linear algebra. The proposed novel method decreases the computational complexity approximately to the half compared with RRQR methods keeping the same performance. Computer simulations are also included to demonstrate the effectiveness of the proposed scheme.

Keywords: frequency hopping, channel model, time delay estimation, RRLU, RRQR, MUSIC, LS-ESPRIT

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Authors: Emad K. Jaradat, Ala’a Al-Faqih

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Nonlinear Schrödinger equations are regularly experienced in numerous parts of science and designing. Varieties of analytical methods have been proposed for solving these equations. In this work, we construct an approximate solution for the nonlinear Schrodinger equations, with harmonic oscillator potential, by Elzaki Decomposition Method (EDM). To illustrate the effects of harmonic oscillator on the behavior wave function, nonlinear Schrodinger equation in one and two dimensions is provided. The results show that, it is more perfectly convenient and easy to apply the EDM in one- and two-dimensional Schrodinger equation.

Keywords: non-linear Schrodinger equation, Elzaki decomposition method, harmonic oscillator, one and two-dimensional Schrodinger equation

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Authors: Majid Forghani, Michael Khachay

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In genetics, the impact of neighboring amino acids on a target site is referred as the nearest-neighbor effect or simply neighbor effect. In this paper, a new method called wavelet particle decomposition representing the one-dimensional neighbor effect using wavelet packet decomposition is proposed. The main idea lies in known dependence of wavelet packet sub-bands on location and order of neighboring samples. The method decomposes the value of a signal sample into small values called particles that represent a part of the neighbor effect information. The results have shown that the information obtained from the particle decomposition can be used to create better model variables or features. As an example, the approach has been applied to improve the correlation of test and reference sequence distance with titer in the hemagglutination inhibition assay.

Keywords: antigenic variants, neighbor effect, wavelet packet, wavelet particle decomposition

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Authors: Kazunori Takai, Weng Kaiwei, Sadao Araki, Hideki Yamamoto

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HFC and PFC gases have been commonly and widely used as refrigerant of air conditioner and as etching agent of semiconductor manufacturing process, because of their higher heat of vaporization and chemical stability. On the other hand, HFCs and PFCs gases have the high global warming effect on the earth. Therefore, we have to be decomposed these gases emitted from chemical apparatus like as refrigerator. Until now, disposal of these gases were carried out by using combustion method like as Rotary kiln treatment mainly. However, this treatment needs extremely high temperature over 1000 °C. In the recent year, in order to reduce the energy consumption, a hydrolytic decomposition method using catalyst and plasma decomposition treatment have been attracted much attention as a new disposal treatment. However, the decomposition of fluorine-containing gases under the wet condition is not able to avoid the generation of hydrofluoric acid. Hydrofluoric acid is corrosive gas and it deteriorates catalysts in the decomposition process. Moreover, an additional process for the neutralization of hydrofluoric acid is also indispensable. In this study, the decomposition of C2F6 using zeolite and zeolite/CaO mixture as reactant was evaluated in the dry condition at 923 K. The effect of the chemical structure of zeolite on the decomposition reaction was confirmed by using H-Y, H-Beta, H-MOR and H-ZSM-5. The formation of CaF2 in zeolite/CaO mixtures after the decomposition reaction was confirmed by XRD measurements. The decomposition of C2F6 using zeolite as reactant showed the closely similar behaviors regardless the type of zeolite (MOR, Y, ZSM-5, Beta type). There was no difference of XRD patterns of each zeolite before and after reaction. On the other hand, the difference in the C2F6 decomposition for each zeolite/CaO mixtures was observed. These results suggested that the rate-determining process for the C2F6 decomposition on zeolite alone is the removal of fluorine from reactive site. In other words, the C2F6 decomposition for the zeolite/CaO improved compared with that for the zeolite alone by the removal of the fluorite from reactive site. HMOR/CaO showed 100% of the decomposition for 3.5 h and significantly improved from zeolite alone. On the other hand, Y type zeolite showed no improvement, that is, the almost same value of Y type zeolite alone. The descending order of C2F6 decomposition was MOR, ZSM-5, beta and Y type zeolite. This order is similar to the acid strength characterized by NH3-TPD. Hence, it is considered that the C-F bond cleavage is closely related to the acid strength.

Keywords: hexafluoroethane, zeolite, calcium oxide, decomposition

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Authors: O. Acan, Y. Keskin

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In this study, we will carry out a comparative study between the reduced differential transform method, the adomian decomposition method, the variational iteration method and the homotopy analysis method. These methods are used in many fields of engineering. This is been achieved by handling a kind of 2-Dimensional and forth-order partial differential equations called the Kuramoto–Sivashinsky equations. Three numerical examples have also been carried out to validate and demonstrate efficiency of the four methods. Furthermost, it is shown that the reduced differential transform method has advantage over other methods. This method is very effective and simple and could be applied for nonlinear problems which used in engineering.

Keywords: reduced differential transform method, adomian decomposition method, variational iteration method, homotopy analysis method

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Authors: Y. Xu, L. Xiong, Z. Xu

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In order to protect data privacy, image with sensitive or private information needs to be encrypted before being outsourced to the cloud. However, this causes difficulties in image retrieval and data management. A secure image retrieval method based on orthogonal decomposition is proposed in the paper. The image is divided into two different components, for which encryption and feature extraction are executed separately. As a result, cloud server can extract features from an encrypted image directly and compare them with the features of the queried images, so that the user can thus obtain the image. Different from other methods, the proposed method has no special requirements to encryption algorithms. Experimental results prove that the proposed method can achieve better security and better retrieval precision.

Keywords: secure image retrieval, secure search, orthogonal decomposition, secure cloud computing

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Authors: O. Delage, H. Bencherif, T. Portafaix, A. Bourdier

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The main purpose of time series analysis is to learn about the dynamics behind some time ordered measurement data. Two approaches are used in the literature to get a better knowledge of the dynamics contained in observation data sequences. The first of these approaches concerns time series decomposition, which is an important analysis step allowing patterns and behaviors to be extracted as components providing insight into the mechanisms producing the time series. As in many cases, time series are short, noisy, and non-stationary. To provide components which are physically meaningful, methods such as Empirical Mode Decomposition (EMD), Empirical Wavelet Transform (EWT) or, more recently, Empirical Adaptive Wavelet Decomposition (EAWD) have been proposed. The second approach is to reconstruct the dynamics underlying the time series as a trajectory in state space by mapping a time series into a set of Rᵐ lag vectors by using the method of delays (MOD). Takens has proved that the trajectory obtained with the MOD technic is equivalent to the trajectory representing the dynamics behind the original time series. This work introduces the singular spectrum decomposition (SSD), which is a new adaptive method for decomposing non-linear and non-stationary time series in narrow-banded components. This method takes its origin from singular spectrum analysis (SSA), a nonparametric spectral estimation method used for the analysis and prediction of time series. As the first step of SSD is to constitute a trajectory matrix by embedding a one-dimensional time series into a set of lagged vectors, SSD can also be seen as a reconstruction method like MOD. We will first give a brief overview of the existing decomposition methods (EMD-EWT-EAWD). The SSD method will then be described in detail and applied to experimental time series of observations resulting from total columns of ozone measurements. The results obtained will be compared with those provided by the previously mentioned decomposition methods. We will also compare the reconstruction qualities of the observed dynamics obtained from the SSD and MOD methods.

Keywords: time series analysis, adaptive time series decomposition, wavelet, phase space reconstruction, singular spectrum analysis

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Authors: Ewedafe Simon Uzezi

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In this paper we presented a method based on Domain Decomposition (DD) for parallelization of 1-D Sugarcane Equation on parallel platform with parallel paradigms on Master-Slave platform using Message Passing Interface (MPI). The 1-D Sugarcane Equation was discretized using explicit method of discretization requiring evaluation nof temporal and spatial distribution of temperature. This platform gives better predictions of the effects of temperature distribution of the sugarcane problem. This work presented parallel overheads with overlapping communication and communication across parallel computers with numerical results across different block sizes with scalability. However, performance improvement strategies from the DD on various mesh sizes were compared experimentally and parallel results show speedup and efficiency for the parallel algorithms design.

Keywords: sugarcane, parallelization, explicit method, domain decomposition, MPI

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Authors: R. H. Hwang, J. H. Park, K. B. Yi

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Nitrous oxide (N2O) is now distinguished as an environmental pollutant. N2O is one of the representative greenhouse gases and N2O is produced by both natural and anthropogenic sources. So, it is very important to reduce N2O. N2O abatement processes are various processes such as HC-SCR, NH3-SCR and decomposition process. Among them, decomposition process is advantageous because it does not use a reducing agent. N2O decomposition is a reaction in which N2O is decomposed into N2 and O2. There are noble metals, transition metal ion-exchanged zeolites, pure and mixed oxides for N2O decomposition catalyst. Among the various catalysts, cobalt-based catalysts derived from hydrotalcites gathered much attention because spinel catalysts having large surface areas and high thermal stabilities. In this study, the effect of promoter and K addition on the activity was compared and analyzed. Co3O4 catalysts for N2O decomposition were prepared by co- precipitation method. Ce and Zr were added during the preparation of the catalyst as promoter with the molar ratio (Ce or Zr) / Co = 0.05. In addition, 1 wt% K2CO3 was doped to the prepared catalyst with impregnation method to investigate the effect of K on the catalyst performance. Characterizations of catalysts were carried out with SEM, BET, XRD, XPS and H2-TPR. The catalytic activity tests were carried out at a GHSV of 45,000 h-1 and a temperature range of 250 ~ 375 ℃. The Co3O4 catalysts showed a spinel crystal phase, and the addition of the promoter increased the specific surface area and reduced the particle and crystal size. It was exhibited that the doping of K improves the catalytic activity by increasing the concentration of Co2+ in the catalyst which is an active site for catalytic reaction. As a result, the K-doped catalyst showed higher activity than the promoter added. Also, it was found through experiments that Co2+ concentration and reduction temperature greatly affect the reactivity.

Keywords: Co₃O4, K-doped, N₂O decomposition, promoter

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Authors: Katya Milenova, Penko Nikolov, Irina Stambolova, Plamen Nikolov, Vladimir Blaskov

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In the recent article, a comparison was made between Cu and TiO2 supported catalysts on activated carbon for ozone decomposition reaction. The activated carbon support in the case of TiO2/AC sample was prepared by physicochemical pyrolysis and for Cu/AC samples the supports are chemically modified carbons. The prepared catalysts were synthesized by impregnation method. The samples were annealed in two different regimes-in air and under vacuum. To examine adsorption efficiency of the samples BET method was used. All investigated catalysts supported on chemically modified carbons have higher specific surface area compared to the specific surface area of TiO2 supported catalysts, varying in the range 590÷620 m2/g. The method of synthesis of the precursors had influenced catalytic activity.

Keywords: activated carbon, adsorption, copper, ozone decomposition, TiO2

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Authors: Jiangyong Liu, Xiangxiang Xu, Bote Luo, Xiaoxue Luo, Jiang Zhu, Lingzhi Yi

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To address the problems of non-linearity and high randomness of the original power load sequence causing the degradation of power load forecasting accuracy, a short-term load forecasting method is proposed. The method is based on the Least Square Support Vector Machine optimized by an Improved Sparrow Search Algorithm combined with the Variational Mode Decomposition proposed in this paper. The application of the variational mode decomposition technique decomposes the raw power load data into a series of Intrinsic Mode Functions components, which can reduce the complexity and instability of the raw data while overcoming modal confounding; the proposed improved sparrow search algorithm can solve the problem of difficult selection of learning parameters in the least Square Support Vector Machine. Finally, through comparison experiments, the results show that the method can effectively improve prediction accuracy.

Keywords: load forecasting, variational mode decomposition, improved sparrow search algorithm, least square support vector machine

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Authors: Saad Al-Baddai, Karema Al-Subari, Elmar Lang, Bernd Ludwig

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Empirical mode decomposition (EMD), a new data-driven of time-series decomposition, has the advantage of supposing that a time series is non-linear or non-stationary, as is implicitly achieved in Fourier decomposition. However, the EMD suffers of mode mixing problem in some cases. The aim of this paper is to present a solution for a common type of signals causing of EMD mode mixing problem, in case a signal suffers of an intermittency. By an artificial example, the solution shows superior performance in terms of cope EMD mode mixing problem comparing with the conventional EMD and Ensemble Empirical Mode decomposition (EEMD). Furthermore, the over-sifting problem is also completely avoided; and computation load is reduced roughly six times compared with EEMD, an ensemble number of 50.

Keywords: empirical mode decomposition (EMD), mode mixing, sifting process, over-sifting

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Authors: Sajeda Elbashabsheh, Kamel Al-Khaled

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This paper applies a modified Laplace Adomian decomposition method to solve the time-fractional JaulentMiodek system. The method produce convergent series solutions with easily compatible components. This paper considers the Caputo fractional derivative. The effectiveness and applicability of the method are demonstrated by comparing its results with those of prior studies. Results are presented in tables and figures. These solutions might be imperative and significant for the explanation of some practical physical phenomena. All computations and figures in the work are done using MATHEMATICA. The numerical results demonstrate that the current methods are effective, reliable, and simple to i implement for nonlinear fractional partial differential equations.

Keywords: approximate solutions, Jaulent-Miodek system, Adomian decomposition method, solitons

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Authors: Lili Yang, Jirui Gong, Qinpu Luo, Min Liu, Bo Yang, Zihe Zhang

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Anthropogenic activities have increased nitrogen (N) inputs to grassland ecosystems. Knowledge of the impact of N addition on litter decomposition is critical to understand ecosystem carbon cycling and their responses to global climate change. The aim of this study was to investigate the effects of N addition and litter types on litter decomposition of a semi-arid temperate grassland during growing and non-growing seasons in Inner Mongolia, northern China, and to identify the relation between litter decomposition and C: N: P stoichiometry in the litter-soil continuum. Six levels of N addition were conducted: CK, N1 (0 g Nm−2 yr−1), N2 (2 g Nm−2 yr−1), N3 (5 g Nm−2 yr−1), N4 (10 g Nm−2 yr−1) and N5 (25 g Nm−2 yr−1). Litter decomposition rates and nutrient release differed greatly among N addition gradients and litter types. N addition promoted litter decomposition of S. grandis, but exhibited no significant influence on L. chinensis litter, indicating that the S. grandis litter decomposition was more sensitive to N addition than L. chinensis. The critical threshold for N addition to promote mixed litter decomposition was 10 -25g Nm−2 yr−1. N addition altered the balance of C: N: P stoichiometry between litter, soil and microbial biomass. During decomposition progress, the L. chinensis litter N: P was higher in N2-N4 plots compared to CK, while the S. grandis litter C: N was lower in N3 and N4 plots, indicating that litter N or P content doesn’t satisfy microbial decomposers with the increasing of N addition. As a result, S. grandis litter exhibited net N immobilization, while L. chinensis litter net P immobilization. Mixed litter C: N: P stoichiometry satisfied the demand of microbial decomposers, showed net mineralization during the decomposition process. With the increasing N deposition in the future, mixed litter would potentially promote C and nutrient cycling in grassland ecosystem by increasing litter decomposition and nutrient release.

Keywords: C: N: P stoichiometry, litter decomposition, nitrogen addition, nutrient release

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Authors: Rogelio Luck, Yucheng Liu

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This paper proposes the continuous-time singular value decomposition (SVD) for the impulse response function, a special kind of Green’s functions e⁻⁽ᵗ⁻ ᵀ⁾, in order to find a set of singular functions and singular values so that the convolutions of such function with the set of singular functions on a specified domain are the solutions to the inhomogeneous differential equations for those singular functions. A numerical example was illustrated to verify the proposed method. Besides the continuous-time SVD, a discrete-time SVD is also presented for the impulse response function, which is modeled using a Toeplitz matrix in the discrete system. The proposed method has broad applications in signal processing, dynamic system analysis, acoustic analysis, thermal analysis, as well as macroeconomic modeling.

Keywords: singular value decomposition, impulse response function, Green’s function , Toeplitz matrix , Hankel matrix

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Authors: William Chung

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This paper is to study the use of multiple subproblems in Dantzig-Wolfe decomposition of linear programming (DW-LP). Traditionally, the decomposed LP consists of one LP master problem and one LP subproblem. The master problem and the subproblem is solved alternatively by exchanging the dual prices of the master problem and the proposals of the subproblem until the LP is solved. It is well known that convergence is slow with a long tail of near-optimal solutions (asymptotic convergence). Hence, the performance of DW-LP highly depends upon the number of decomposition steps. If the decomposition steps can be greatly reduced, the performance of DW-LP can be improved significantly. To reduce the number of decomposition steps, one of the methods is to increase the number of proposals from the subproblem to the master problem. To do so, we propose to add a quadratic approximation function to the LP subproblem in order to develop a set of approximate-LP subproblems (multiple subproblems). Consequently, in each decomposition step, multiple subproblems are solved for providing multiple proposals to the master problem. The number of decomposition steps can be reduced greatly. Note that each approximate-LP subproblem is nonlinear programming, and solving the LP subproblem must faster than solving the nonlinear multiple subproblems. Hence, using multiple subproblems in DW-LP is the tradeoff between the number of approximate-LP subproblems being formed and the decomposition steps. In this paper, we derive the corresponding algorithms and provide some simple computational results. Some properties of the resulting algorithms are also given.

Keywords: approximate subproblem, Dantzig-Wolfe decomposition, large-scale models, multiple subproblems

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Authors: Ahmad Awajan, Sadam Al Wadi

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In this study, a hybrid method based on Empirical Mode Decomposition and Holt-Winter (EMD-HW) is used to forecast Amman stock market data. First, the data are decomposed by EMD method into Intrinsic Mode Functions (IMFs) and residual components. Then, all components are forecasted by HW technique. Finally, forecasting values are aggregated together to get the forecasting value of stock market data. Empirical results showed that the EMD- HW outperform individual forecasting models. The strength of this EMD-HW lies in its ability to forecast non-stationary and non- linear time series without a need to use any transformation method. Moreover, EMD-HW has a relatively high accuracy comparing with eight existing forecasting methods based on the five forecast error measures.

Keywords: Holt-Winter method, empirical mode decomposition, forecasting, time series

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Authors: M. Sneha Reddy, M. Arun Kumar, V. Kameswara Rao

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Chromites are binary transition metal oxides with a general formula of ACr₂O₄, where A = Mn²⁺, Fe²⁺, Co²⁺, Ni²⁺, and Cu²⁺. Chromites have a normal-type spinel structure with interesting applications in the areas of applied physics, material sciences, and geophysics. They have attracted great consideration because of their unique physicochemical properties and tremendous technological applications in nanodevices, sensor elements, and high-temperature ceramics with useful optical properties. Copper chromite is one of the most efficient spinel oxides, having pronounced commercial application as a catalyst in various chemical reactions like oxidation, hydrogenation, alkylation, dehydrogenation, decomposition of organic compounds, and hydrogen production. Apart from its usage in chemical industries, CuCr₂O₄ finds its major application as a burn rate modifier in solid propellant processing for space launch vehicles globally. Herein we synthesized the nanoparticles of copper chromite using the co-precipitation method. The synthesized nanoparticles were characterized by XRD, TEM, SEM, BET, and TG-DTA. The synthesized nanoparticles of copper chromites were used as a catalyst for the thermal decomposition of various high-energy materials.

Keywords: copper chromite, coprecipitation method, high energy materials, catalytic thermal decomposition

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Authors: Salma Krafessi

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The financial markets have a multifaceted, intricate environment, and enormous volumes of data are produced every day. To find investment possibilities, possible fraudulent activity, and market oddities, accurate anomaly identification in this data is essential. Conventional methods for detecting anomalies frequently fail to capture the complex organization of financial data. In order to improve the identification of abnormalities in financial time series data, this study presents Tucker Decomposition as a reliable multi-way analysis approach. We start by gathering closing prices for the S&P 500 index across a number of decades. The information is converted to a three-dimensional tensor format, which contains internal characteristics and temporal sequences in a sliding window structure. The tensor is then broken down using Tucker Decomposition into a core tensor and matching factor matrices, allowing latent patterns and relationships in the data to be captured. A possible sign of abnormalities is the reconstruction error from Tucker's Decomposition. We are able to identify large deviations that indicate unusual behavior by setting a statistical threshold. A thorough examination that contrasts the Tucker-based method with traditional anomaly detection approaches validates our methodology. The outcomes demonstrate the superiority of Tucker's Decomposition in identifying intricate and subtle abnormalities that are otherwise missed. This work opens the door for more research into multi-way data analysis approaches across a range of disciplines and emphasizes the value of tensor-based methods in financial analysis.

Keywords: tucker decomposition, financial markets, financial engineering, artificial intelligence, decomposition models

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Authors: Latha Subbiah, Dhanalakshmi Samiappan

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In this paper, we propose denoising Common Carotid Artery (CCA) B mode ultrasound images by a decomposition approach to curvelet thresholding and automatic segmentation of the intima media thickness and adventitia boundary. By decomposition, the local geometry of the image, its direction of gradients are well preserved. The components are combined into a single vector valued function, thus removes noise patches. Double threshold is applied to inherently remove speckle noise in the image. The denoised image is segmented by active contour without specifying seed points. Combined with level set theory, they provide sub regions with continuous boundaries. The deformable contours match to the shapes and motion of objects in the images. A curve or a surface under constraints is developed from the image with the goal that it is pulled into the necessary features of the image. Region based and boundary based information are integrated to achieve the contour. The method treats the multiplicative speckle noise in objective and subjective quality measurements and thus leads to better-segmented results. The proposed denoising method gives better performance metrics compared with other state of art denoising algorithms.

Keywords: curvelet, decomposition, levelset, ultrasound

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